Imagine how you'd answer these questions:
Which loans above 100M have a MFN sunset period less than 6 months?
What do those loans say about dividends in negative covenants?
With 100+ pre-extracted data points from Credit Agreements filed with SEC, you can search and filter the vast collection of agreements to find exactly what you need to help you with negotiation.
SifterAI SEC Credit Agreement collection offers you the most comprehensive way to look at a wide variety of agreements and find a needle in the haystack that will be invaluable for you to structure a new deal.
“We looked at a lot of different AI tools to help us search across large sets of documents and surface particular provisions from those documents. We were ideally looking for a tool that would enable us to extract data points from contracts without needing to do a ton of post-processing to make the data usable for analytics.”
"We found the natural language search interface and human-in-the-loop review tools that SifterAI offered to be pretty amazing. Unlike most of the tools we had tried—which typically only returned blocks of text, and, even then, often only after extensive training—SifterAI returns structured answers to our questions in the format we’re looking for."
"SifterAI data points will allow our attorneys to better advise our clients on what we’re seeing in the market."
Our mission is to empower organizations to unlock the limitless potential of data in unstructured text.
We are a team of researchers, technologists and industry experts determined to help firms succeed in their mission to be more data driven.
We deploy the latest AI advances in natural language understanding and large language models for tackling the enormous challenge of extracting data from lengthy documents with great accuracy.
We care deeply about our customers. Customers have direct access to our engineers and we excel at post sales customer service and partnership.
Co-founder and CEO Ambika Sukla led the AI Center of Excellence at Morgan Stanley where he explored solutions for large scale data extraction from complex and lengthy business documents.
After spending months on unsuccessful pilots with third-party products, tedious hand crafted homegrown solutions, and training highly limited custom models, Ambika felt the need for a user friendly way to query large number of documents for data.
He saw the opportunity to harness the power of large language models and developed SifterAI to make this vision possible.
